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Nanoformulation of Curcuma longa Root Extract and Evaluation of Its Dissolution Potential.

Amjad HussainFaisal AttiqueSyed Ali Raza NaqviAkbar AliMuhammad IbrahimHidayat HussianFatiqa ZafarRana Saqib IqbalMuhammad Adnan AyubMohammed A AssiriMuhammad ImranShaheed Ullah
Published in: ACS omega (2022)
Medicinal plants have been widely used for therapeutic purposes for a long time, but they have been found to have some major issues such as low water solubility and bioavailability. In the present study, the nanoformulation of Curcuma longa L. plant extract was prepared to enhance its dissolution potential and biological activities. For the formulation of the nanosuspension, an ethanolic extract of C. longa was prepared through Soxhlet extraction using the nanoformulation technique. The nanosuspensions were formulated using four different stabilizers, namely sodium lauryl sulfate (SLS), hydroxy propyl methyl cellulose (HPMC), poly(vinyl alcohol) (PVA), and polysorbate-80 (P-80). The scanning electron microscopy (SEM), polydispersity index, and ζ potential were used for characterization of the nanoformulation. Among all of these, the surfactant stabilizer SLS was found to be the best. The average particle size of the selected optimized nanosuspension was found to be 308.2 nm with a polydispersity index (PDI) value of 0.330. The ζ potential value of the optimized nanosuspension was recorded at -33.3 mV. The SEM image indicated that the particles were slightly agglomerated, which may have occurred during lyophilization of the nanosuspension. The highest dissolution rate recorded at pH = 7 was 192.32 μg/mL, which indicates pH = 7 as the most appropriate condition for the dissolution of the C. longa nanosuspension. The antioxidant, antimicrobial, and antifungal activities of the optimized nanosuspension were also determined with regard to the coarse plant extract. The study findings suggested that the nanoprecipitation approach helps in enhancing the dissolution potential and biological activities of C. longa root extract.
Keyphrases
  • oxidative stress
  • anti inflammatory
  • electron microscopy
  • human health
  • high resolution
  • risk assessment
  • drug delivery
  • machine learning
  • molecular dynamics simulations
  • ionic liquid